Abnormal visual representations associated with confusion of perceived facial expression in schizophrenia with social anxiety disorder
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Bibliographic record
Abstract
Deficits in social functioning are especially severe amongst schizophrenia individuals with the prevalent comorbidity of social anxiety disorder (SZ&SAD). Yet, the mechanisms underlying the recognition of facial expression of emotions-a hallmark of social cognition-are practically unexplored in SZ&SAD. Here, we aim to reveal the visual representations SZ&SAD (n = 16) and controls (n = 14) rely on for facial expression recognition. We ran a total of 30,000 trials of a facial expression categorization task with Bubbles, a data-driven technique. Results showed that SZ&SAD's ability to categorize facial expression was impared compared to controls. More severe negative symptoms (flat affect, apathy, reduced social drive) was associated with more impaired emotion recognition ability, and with more biases in attributing neutral affect to faces. Higher social anxiety symptoms, on the other hand, was found to enhance the reaction speed to neutral and angry faces. Most importantly, Bubbles showed that these abnormalities could be explained by inefficient visual representations of emotions: compared to controls, SZ&SAD subjects relied less on fine facial cues (high spatial frequencies) and more on coarse facial cues (low spatial frequencies). SZ&SAD participants also never relied on the eye regions (only on the mouth) to categorize facial expressions. We discuss how possible interactions between early (low sensitivity to coarse information) and late stages of the visual system (overreliance on these coarse features) might disrupt SZ&SAD's recognition of facial expressions. Our findings offer perceptual mechanisms through which comorbid SZ&SAD impairs crucial aspects of social cognition, as well as functional psychopathology.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it